Figure 1. True mean (+/- SE) physiology of T0 coral fragments (one per colony; n = 8-14) denoted by black cross with (A) individual colony physiology denoted by coloured shape or (B) native reef environment.
Figure 2. True mean (+/- SE) T0 and T90 coral fragment physiology of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia with individual coral fragment physiology denoted by points. T0 corals are represented by green stars. Blue denotes 28C, red denotes 31C, and shape corresponds to pCO2 treatment conditions of T90 fragments.
Figure 1. True mean (+/- SE) physiology of T0 coral fragments (one per colony; n = 8-14) denoted by black cross with individual colony physiology denoted by coloured shape (triangle = offshore, circle = inshore).
Figure 2. True mean (+/- SE) T0 and T90 coral fragment physiology of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia with individual coral fragment physiology denoted by points. T0 corals are represented by green stars. Blue denotes 28\(^\circ\)C, red denotes 31\(^\circ\)C, and shape corresponds to pCO2 treatment conditions of T90 fragments.
Figure 3. Modelled 95% confidence interval of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia physiology with individual coral fragment physiology denoted by points. Blue denotes 28C and red denotes 31C, with pCO2 treatment along the x axis.
| comparison | R2 | p.value | comparison | R2 | p.value | comparison | R2 | p.value | comparison | R2 | p.value |
|---|---|---|---|---|---|---|---|---|---|---|---|
| chla v sum | 0.116 | 0.0005 | chla v sum | 0.327 | 0e+00 | chla v sum | 0.317 | 0.0000 | chla v sum | 0.029 | 0.1651 |
| chla v red | 0.136 | 0.0002 | chla v red | 0.436 | 0e+00 | chla v red | 0.291 | 0.0000 | chla v red | 0.023 | 0.1909 |
| chla v blue | 0.056 | 0.0130 | chla v blue | 0.133 | 5e-04 | chla v blue | 0.276 | 0.0000 | chla v blue | 0.028 | 0.1681 |
| chla v green | 0.122 | 0.0004 | chla v green | 0.364 | 0e+00 | chla v green | 0.316 | 0.0000 | chla v green | 0.031 | 0.1591 |
| den v sum | 0.217 | 0.0000 | den v sum | 0.388 | 0e+00 | den v sum | -0.015 | 0.9279 | den v sum | -0.017 | 0.5217 |
| den v red | 0.234 | 0.0000 | den v red | 0.399 | 0e+00 | den v red | -0.015 | 0.9936 | den v red | -0.026 | 0.7067 |
| den v blue | 0.143 | 0.0001 | den v blue | 0.192 | 0e+00 | den v blue | -0.015 | 0.9747 | den v blue | -0.001 | 0.3329 |
| den v green | 0.218 | 0.0000 | den v green | 0.390 | 0e+00 | den v green | -0.014 | 0.8190 | den v green | -0.016 | 0.4935 |
Figure 4. Text goes here
Figure 5. Text goes here
Figure 2. Modelled 95% confidence interval of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia physiology with individual coral fragment physiology denoted by points. Blue denotes 28C and red denotes 31C, with pCO2 treatment along the x axis.
| comparison | R2 | p.value | comparison | R2 | p.value | comparison | R2 | p.value | comparison | R2 | p.value |
|---|---|---|---|---|---|---|---|---|---|---|---|
| chla v sum | 0.116 | 0.0005 | chla v sum | 0.327 | 0e+00 | chla v sum | 0.317 | 0.0000 | chla v sum | 0.029 | 0.1651 |
| chla v red | 0.136 | 0.0002 | chla v red | 0.436 | 0e+00 | chla v red | 0.291 | 0.0000 | chla v red | 0.023 | 0.1909 |
| chla v blue | 0.056 | 0.0130 | chla v blue | 0.133 | 5e-04 | chla v blue | 0.276 | 0.0000 | chla v blue | 0.028 | 0.1681 |
| chla v green | 0.122 | 0.0004 | chla v green | 0.364 | 0e+00 | chla v green | 0.316 | 0.0000 | chla v green | 0.031 | 0.1591 |
| den v sum | 0.217 | 0.0000 | den v sum | 0.388 | 0e+00 | den v sum | -0.015 | 0.9279 | den v sum | -0.017 | 0.5217 |
| den v red | 0.234 | 0.0000 | den v red | 0.399 | 0e+00 | den v red | -0.015 | 0.9936 | den v red | -0.026 | 0.7067 |
| den v blue | 0.143 | 0.0001 | den v blue | 0.192 | 0e+00 | den v blue | -0.015 | 0.9747 | den v blue | -0.001 | 0.3329 |
| den v green | 0.218 | 0.0000 | den v green | 0.390 | 0e+00 | den v green | -0.014 | 0.8190 | den v green | -0.016 | 0.4935 |
**Notes:**
Plotting sum colour intensity metrics
| Carbohydrate | Protein | Symbiont Density | Chlorophyll a | Colour Intensity | |
|---|---|---|---|---|---|
| Temperature | 0.0022 | 0.7612 | 0.1781 | 0.0063 | 0.0405 |
| 280 pCO2 | 0.6774 | 0.7228 | 0.7211 | 0.5132 | 0.2808 |
| 700 pCO2 | 0.2133 | 0.3481 | 0.1362 | 0.0067 | 0.2041 |
| 2800 pCO2 | 0.8782 | 0.2430 | 0.0001 | 0.0000 | 0.0004 |
| Reef Environment | 0.6175 | 0.2905 | 0.2580 | 0.1641 | 0.0011 |
| Temperature x Reef | NA | 0.0660 | 0.0540 | NA | NA |
| Carbohydrate | Protein | Symbiont Density | Chlorophyll a | Colour Intensity | |
|---|---|---|---|---|---|
| Temperature | 0.0006 | 0.0001 | 0.0005 | 0.0002 | 0.0000 |
| 280 pCO2 | 0.4235 | 0.1194 | 0.8763 | 0.0645 | 0.6704 |
| 700 pCO2 | 0.3631 | 0.7584 | 0.1746 | 0.1886 | 0.2143 |
| 2800 pCO2 | 0.6688 | 0.9277 | 0.0973 | 0.1155 | 0.3556 |
| Reef Environment | 0.1361 | 0.5369 | 0.0001 | 0.0053 | 0.0387 |
| Temperature x Reef | NA | NA | 0.0424 | NA | 0.0367 |
| Carbohydrate | Protein | Symbiont Density | Chlorophyll a | Colour Intensity | |
|---|---|---|---|---|---|
| Temperature | 0.0492 | 0.0739 | 0.4838 | 0.0359 | 0.0004 |
| 280 pCO2 | 0.6023 | 0.4606 | 0.5614 | 0.6830 | 0.0523 |
| 700 pCO2 | 0.0196 | 0.1696 | 0.2129 | 0.0058 | 0.0046 |
| 2800 pCO2 | 0.0121 | 0.0099 | 0.5500 | 0.0008 | 0.1385 |
| Reef Environment | 0.1508 | 0.2345 | 0.5783 | 0.8997 | 0.4500 |
| Temperature x 280 pCO2 | NA | NA | NA | 1.1949138702567e-09 | NA |
| Temperature x 700 pCO2 | NA | NA | NA | 2.13430417166503e-05 | NA |
| Temperature x 2800 pCO2 | NA | NA | NA | 0.231211071936069 | NA |
| Carbohydrate | Protein | Symbiont Density | Chlorophyll a | Colour Intensity | |
|---|---|---|---|---|---|
| Temperature | 0.3819 | 0.5284 | 0.3287 | 0.0058 | 0.0000 |
| 280 pCO2 | 0.2115 | 0.4150 | 0.6347 | 0.4250 | 0.8840 |
| 700 pCO2 | 0.6568 | 0.5509 | 0.3582 | 0.2885 | 0.0150 |
| 2800 pCO2 | 0.8366 | 0.7393 | 0.3587 | 0.7004 | 0.0535 |
| Reef Environment | 0.6180 | 0.9055 | 0.3112 | 0.4654 | 0.0586 |
T90 plot of all parameters by reefzone
PCA of physiology at T90
##
## Call:
## lm(formula = pro ~ carb, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68459 -0.12391 -0.04553 0.09898 0.60632
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.10883 0.01890 5.757 2.01e-08 ***
## carb 0.28467 0.02132 13.350 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.187 on 320 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3577, Adjusted R-squared: 0.3557
## F-statistic: 178.2 on 1 and 320 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = chla ~ den, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -134.15 -43.09 -20.60 26.54 479.49
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 59.291 5.221 11.357 < 2e-16 ***
## den 5.959 1.361 4.378 1.63e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 69.35 on 319 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.05667, Adjusted R-squared: 0.05371
## F-statistic: 19.16 on 1 and 319 DF, p-value: 1.628e-05
##
## Call:
## lm(formula = sum_bw5 ~ den, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -360.06 -77.49 28.33 105.07 185.65
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -239.8862 10.3759 -23.120 <2e-16 ***
## den 0.2194 2.5581 0.086 0.932
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 128.7 on 276 degrees of freedom
## (45 observations deleted due to missingness)
## Multiple R-squared: 2.666e-05, Adjusted R-squared: -0.003596
## F-statistic: 0.007358 on 1 and 276 DF, p-value: 0.9317
##
## Call:
## lm(formula = sum_bw5 ~ chla, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -314.37 -70.34 24.01 100.32 189.37
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -291.27978 10.31268 -28.245 < 2e-16 ***
## chla 0.66159 0.09593 6.897 3.58e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 118.9 on 278 degrees of freedom
## (43 observations deleted due to missingness)
## Multiple R-squared: 0.1461, Adjusted R-squared: 0.143
## F-statistic: 47.57 on 1 and 278 DF, p-value: 3.581e-11
##
## Call:
## lm(formula = pro ~ chla, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84382 -0.15670 -0.01467 0.13149 0.66354
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1955664 0.0161970 12.07 <2e-16 ***
## chla 0.0016608 0.0001573 10.56 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2007 on 321 degrees of freedom
## Multiple R-squared: 0.2578, Adjusted R-squared: 0.2555
## F-statistic: 111.5 on 1 and 321 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = carb ~ chla, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9398 -0.3286 -0.1149 0.2597 2.2662
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5493115 0.0367617 14.943 < 2e-16 ***
## chla 0.0025514 0.0003567 7.152 5.84e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4552 on 320 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1378, Adjusted R-squared: 0.1351
## F-statistic: 51.16 on 1 and 320 DF, p-value: 5.839e-12
##
## Call:
## lm(formula = pro ~ rate, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.61621 -0.14542 -0.04558 0.11987 0.68780
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.24088 0.01288 18.70 <2e-16 ***
## rate 0.17596 0.01402 12.55 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1939 on 278 degrees of freedom
## (43 observations deleted due to missingness)
## Multiple R-squared: 0.3618, Adjusted R-squared: 0.3595
## F-statistic: 157.6 on 1 and 278 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = carb ~ rate, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.07630 -0.28281 -0.05503 0.16522 2.08199
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.59443 0.02932 20.273 < 2e-16 ***
## rate 0.23129 0.03190 7.251 4.15e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.441 on 277 degrees of freedom
## (44 observations deleted due to missingness)
## Multiple R-squared: 0.1595, Adjusted R-squared: 0.1565
## F-statistic: 52.58 on 1 and 277 DF, p-value: 4.145e-12
##
## Call:
## lm(formula = chla ~ rate, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -157.09 -37.94 -11.42 23.36 417.72
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 58.027 4.112 14.11 <2e-16 ***
## rate 49.589 4.476 11.08 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 61.91 on 278 degrees of freedom
## (43 observations deleted due to missingness)
## Multiple R-squared: 0.3063, Adjusted R-squared: 0.3038
## F-statistic: 122.8 on 1 and 278 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = den ~ rate, data = df.90b)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7465 -1.9950 -0.8537 0.6905 19.5315
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.6506 0.2023 13.103 <2e-16 ***
## rate 0.1482 0.2196 0.675 0.5
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.025 on 276 degrees of freedom
## (45 observations deleted due to missingness)
## Multiple R-squared: 0.001647, Adjusted R-squared: -0.00197
## F-statistic: 0.4553 on 1 and 276 DF, p-value: 0.5004